Scopus
Using adaptive neuro-fuzzy inference system, artificial neural network and response surface method to optimize overall equipment effectiveness for an automotive supplier company
Journal of Multiple Valued Logic and Soft Computing · Ocak 2017
Makale Bilgileri
DergiJournal of Multiple Valued Logic and Soft Computing
Yayın TarihiOcak 2017
Cilt / Sayfa28 · 375-407
Scopus ID2-s2.0-85018741808
Özet
Total Productive Maintenance (TPM) is a successful technique that is important in identifying the success and overall effectiveness of the manufacturing process for long term economic viability of business. Overall equipment effectiveness (OEE) is commonly used and wellaccepted metric for TPM implementation in many manufacturing industries. As OEE is an important performance measure for effectiveness of any equipment, careful analysis is required to know the effect of various components. An attempt has been done in this research to predict the OEE by using simulation software. The objective is to identify an optimal OEE level to maximize the time between failures and simultaneously minimize the mean repair time. The process of OEE is optimized by using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference system (ANFIS) to identify optimized zone for maximizing output. Finally it is determined the feasible values of inputs using Sequential Quadratic Programming (SQP) algorithm based on trained ANFIS predictive model. The result from this study can be used the inconvenient impact of the failures on the production process, it is strongly recommended to upgrade the operation management, i.e. TPM program, capacity analysis, parts replacement decisions, training programs for technicians/operators, spare parts requirement etc.
Yazarlar (3)
1
Ebru Turanoglu Bekar
2
Mehmet Cakmakci
3
Cengiz Kahraman
Anahtar Kelimeler
Adaptive neuro- fuzzy inference system (ANFIS)
Artificial neural network (ANN)
Overall equipment effectiveness (OEE) level
Response surface methodology (RSM)
Kurumlar
Dokuz Eylül Üniversitesi
Izmir Turkey
İstanbul Teknik Üniversitesi
Istanbul Turkey
Metrikler
3
Atıf
3
Yazar
4
Anahtar Kelime